atlas

Research map / Learning theory and algorithms / Combinatorial and search optimization

Was Fixing This Really That Hard? On the Complexity of Correcting HTN Domains

AAAI 2023 · Learning theory and algorithms › Combinatorial and search optimization · approach: Classical and HTN planning · 5 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Allow any nonempty subset of action insertion, action deletion, and ordering-constraint deletionHTN domain correction for white-list plans · CHANGEXcomputational complexity: NP-completeMixed
Supply decomposition forests for the white-list plansHTN domain correction · CHANGEDFXcomputational complexity: NP-hardMixed
Supply decomposition forests and task-to-plan mappings, while disallowing action insertionHTN domain correction · CHANGEDFMXcomputational complexity: in PHelped
Allow action insertion even when decomposition forests and task-to-plan mappings are suppliedHTN domain correction · CHANGEDFMXcomputational complexity: NP-hardHurt
Require both white-list acceptance and black-list rejectionHTN domain correction · CHANGEWBXcomputational complexity: at least NP-hard; in Σp₂Mixed
Test whether an action sequence linearises a partially ordered task networkVALIDSEQ · VALIDSEQcomputational complexity: NP-completeMixed

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy